Abstract

Abstract. Covert channels inside DNS allow evasion of networks which only provide a restricted access to the Internet. By encapsulating data inside DNS requests and replies exchanged with a server located outside the restricted network, several existing implementations provide either an IP over DNS tunnel, or a socket-like service (TCP over DNS). This paper contributes a detailed overview of the challenges faced by the design of such tunnels, and describes the existing implementations. Then, it introduces TUNS, our prototype of an IP over DNS tunnel, focused on simplicity and protocol compliance. Comparison of TUNS and the other implementations showed that this approach is successful: TUNS works on all the networks we tested, and provides reasonable performance despite its use of less efficient encapsulation techniques, especially when facing degraded network conditions.

Scheduling computational jobs with data-sets dependencies is an important challenge of edge computing infrastructures. Although several strategies have been proposed, they have been evaluated through ad-hoc simulator extensions that are, when available, usually not maintained. This is a critical problem because it prevents researchers to -easily-perform fair comparisons between different proposals.In this paper, we propose to address this limitation by presenting a simulation engine dedicated to the evaluation and comparison of scheduling and data movement policies for edge computing use-cases. Built upon the Batsim/SimGrid toolkit, our tool includes an injector that allows the simulator to replay a series of events captured in real infrastructures. It also includes a controller that supervises storage entities and data transfers during the simulation, and a plug-in system that allows researchers to add new models to cope with the diversity of edge computing devices.We demonstrate the relevance of such a simulation toolkit by studying two scheduling strategies with four data movement policies on top of a simulated version of the Qarnot Computing platform, a production edge infrastructure based on smart heaters. We chose this use-case as it illustrates the heterogeneity as well as the uncertainties of edge infrastructures.Our ultimate goal is to gather industry and academics around a common simulator so that efforts made by one group can be factorised by others.

The Petaflow project aims to contribute to the use of high performance computational resources to the benefit of society. To this goal the emergence of adequate information and communication technologies with respect to high performance computing-networking-visualisation and their mutual awarness is required. The developed technology and algorithms are presented and applied to a real peta-scale data intensive scientific problem with social importance, i.e. human upper airflow modeling.